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  • Is the ABH FRC validated?

    The ABH FRC was validated in a Northern California Kaiser Permanente database of over 94,000 women14 and with a cohort of men over 5800 men15.

  • On what data is this model based?

    The American Bone Health Fracture Risk Calculator (ABH FRC) uses several easily ascertained risk factors plus bone mineral density (BMD) to calculate 10-year absolute fracture risk. The model begins by assigning the average fracture rate based on the patient’s age. These population rates come from a publication that used US hospital discharge data for 2006.The model calculates differences between the individual and the reference population in several clinical risk factors including bone mineral density (BMD). Each risk factor’s relative risk is used to modify the expected fracture rate. The risk factors and relative risks are closely aligned to those used in FRAX™ 2.

  • Why use a 10 year risk model?

    Excellent risk-assessment models 3,4 exist for other diseases and have been translated into computer software that calculates absolute risk of an “event” from multiple variables. These models include the one widely used to predict 5- and 10-year risks for breast cancer 3 and the National Cholesterol Education Program’s model for predicting 10-year risk of coronary heart disease.4 Both models have been used in developing best practice guidelines, are widely recommended to guide treatment decisions, and are well accepted by health care providers. Cost-effectiveness analyses 5 and treatment recommendations based on these analyses 6 have now been published for osteoporosis drugs.

  • Are there other web-based fracture risk models?

    The World Health Organization FRAX™ model essentially replaces all previous web-based models because it has been extensively validated in populations around the world.

  • How does the current ABH FRC model differ from the WHO FRAX™ model?

    The ABH FRC model and FRAX™ model use the same input variables, the same base fracture rates, and the same relative risks (multipliers).2 Both can be applied to men and 4 different ethnicities. Both produce results of the 10-year risk of hip and any one of 4 fractures (hip, wrist, humerus, clinically identified spine). One major difference is that the ABH FRC provides a graphic display of risk, comparing it to the expected risk, and categorizes it as low, moderate, or high. This is beneficial as a shared decision-making tool for patients and their health care providers.

    A second difference is the FRAX™ model incorporates mortality into their algorythm, meaning that as a person ages in FRAX, their risk of fracture goes down.

    Users of these models should get very similar but not identical results.

  • Don't the types of fracture change with age?

    The ABH FRC and FRAX™ models provide 10-year absolute fracture risk for a hip fracture and for any one of 4 fractures (hip, spine, humerus, or wrist). The mix of fractures changes with age: at 45-49 years, hip fractures constitute only 7% but increase to 50% at 75 years.7 In contrast, the proportion of wrist fractures decreases with age, from 60% among the younger group to 26% among the older.

  • Why weren't other fractures included?

    Both the ABH FRC and FRAX™ models include four clinical osteoporotic fracture locations (i.e., spine, wrist, humerus, and hip) for several reasons: low BMD is a demonstrated risk factor for these fracture types;7 these fractures constitute the majority of osteoporotic (fragility-type or low impact) fractures;8 accurate rates of fracture incidence for the age range of interest were available from reliable published data1 and these fractures are costly to treat and can seriously alter quality of life.9

  • Why aren't other clinical risk factors included?

    Both the ABH FRC and FRAX™ models aim to keep the model data entry simple and in an easily understood format. Both use risk factors whose individual contributions to fracture risk have been estimated in large epidemiologic studies using multivariable models; the risk factors are the same as those used in cost-effectiveness analyses.5

  • Won't the WHO FRAX™ model replace the ABH FRC model?

    The WHO model is the standard in the field and has been incorporated into BMD reporting. In the ABH FRC, we have tried, as much as possible, to use the rates and relative risks that appear in the WHO model.2 The ABH FRC adds graphic display and categorization of risk—that should be helpful in discussing prevention and treatment strategies and risks and benefits of treatment.

  • How should this model help patients make decisions?

    Models could promote awareness of the need for treatment among overlooked women in their 60s who have a number of risk factors but no clinically apparent osteoporosis (i.e. T-score not <-2.5). Fracture models appear to have the greatest value in solving the common clinical conundrum of low bone density (osteopenia) in healthy, early postmenopausal women. Giving a patient her absolute risk and discussing risk reduction expected from treatment in an easily understandable context enriches the quality and accuracy of information both health care providers and patients use for making decisions.

  • Can the model be used for men? For different ethnicities?

    Both the ABH FRC and FRAX™ can be used for men and for 4 different ethnicities (Caucasian, Hispanic, Black, Asian). Simply select gender and race/ethnicity in the input fields.

  • What if the patient is being treated for osteoporosis?

    This model is based on fracture rates in untreated women and does not account for the effects of being on an osteoporosis treatment. Estimates of the fracture risk reduction from regular long-term bisphosphonate therapy are in the order of 25-35%. 5,6,10 Leslie et. al. 11, on the basis of a large population study, concluded that “the FRAX tool can be used to predict fracture probability in women currently or previously treated for osteoporosis”. In that study, bisphosphonate use did not substantially change the categorization of women in the population to low, medium, or high risk.

  • What about falls and frailty?

    This ABH FRC does not capture the additional risks of falls and frailty because there are not studies that provide a relative risk for fractures based on these variables.

  • Why were these thresholds (low, moderate, high) chosen?

    Cost-effectiveness analyses and treatment guidelines based on US costs and fracture rates have been published.5,6 The thresholds cited are 3% or more for 10-year risk of hip fracture and 20% or more for 10-year risk of any one of 4 fractures. The ABH FRC shows rates above the 20% threshold as high risk, includes a moderate risk zone (10-20%), as well as a low risk zone (<10%). These same percentage cut points are used for cardiovascular disease (National Cholesterol Education Program)4 and have been adopted by expert osteoporosis groups.12 In counseling patients about the risks and benefits of treatments for osteoporosis, we find that most individuals start to worry about their risk when it reaches “double digits” and 20% (1 in 5) is usually of great concern. Providing absolute risks rather than relative risks allows patients to make better informed decisions about the risks of fracture and the benefits of medicines to reduce their risk.13

  • References

    1. Ettinger B, Black DM, Dawson-Hughes B, et al. Updated fracture incidence rates for the US version of FRAX. Osteoporos Int 21:25-33, 2010.
    2. Ettinger B, Liu H, Blackwell T, et al. Validation of FRC, a fracture risk assessment tool, in a cohort of older men: The Osteoporotic Fractures in Men Study. J Clin Densitom 2012 [epub ahead of print]
    3. Benichou J. A computer program for estimating individualized probabilities of breast cancer. Comput Biomed Res 1993; 26:373-82.
    4. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001; 285:2486-97.
    5. Tosteson ANA, Melton II LJ, Dawson-Hughes B, Baim S, Favus MJ, Khosla S, Lindsay RL. Cost-effective osteoporosis treatment thresholds: the United States perspective. Osteoporos Int 2008; 19:437-47.
    6. Dawson-Hughes B, Tosteson ANA, Melton III LJ, Baim S, Favus ML, Khosla S, Lindsay RL. Implications of absolute fracture risk assessment for osteoporosis practice guidelines in the USA. Osteoporos Int 2008; 19:449-58.
    7. Ettinger B, Hillier TA, Pressman AR, Che M, Hanley DA. Simple computer model for calculating 5-year osteoporotic fracture risk in postmenopausal women. J Women’s Health 2005; 14:159-171.
    8. Seeley DG, Browner WS, Nevitt MC, Genant HK, Scott JC, Cummings SR. Which fractures are associated with low appendicular bone mass in elderly women? Study of Osteoporotic Fractures Research Group. Ann Intern Med 1991; 115:837-42.
    9. Ray NF, Chan JK, Thamer M, Melton LJ 3rd. Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation. J Bone Miner Res 1997; 12:24-35.
    10. Kanis JA, Borgstrom F, Zethraeus N, Johnell O, Oden A, Jonsson B. Intervention thresholds for osteoporosis in the UK. Bone 2005; 36: 22-32.
    11. Leslie WD, Lix LM, Johansson H, et al. Does osteoporosis therapy invalidate FRAX for fracture prediction? J Bone Miner Res 2012; doi 10.1002/jbmr.1582 [epub ahead of print]
    12. Siminoski K, Leslie WD, Frame H, et al. Recommendations for bone mineral density reporting in Canada. Can Assoc Radiol J 2005; 56:178-88.
    13. Hux JE, Naylor CD. Communicating the benefits of chronic preventive therapy: does the format of efficacy data determine patients’ acceptance of treatment? Med Decis Making 1995; 15:152-7.
    14. Lo J, Pressman A. Fracture Risk Tool Validation in an Integrated Healthcare Delivery System. AJMC 3/2011.
    15. Ettinger B, Liu, Hau. Validation of FRC, a Fracture Risk Assessment Tool, in a Cohort of Older Men: The Osteoporotic Fractures in Men Study. J Clin Dens. 2012